Real estate risk is defined as the uncertainty in achieving the investor’s expected return on the basis of which the property was acquired. This risk is multi-dimensional and may stem from international, national, regional, local market and property-specific factors. All these factors can and may affect the rental income that can be earned by a property and its value, and, therefore, the investor’s return.
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The most common measure of real estate risk featured in many studies is the standard deviation of historical returns. The standard deviation is the typical measure of the volatility of historical return series or a price series (e.g. the volatility of the share price of a company).
The mathematical formula of the standard deviation can be found in many statistical books, but we don’t present it here as in practice it is rarely used as this measure can be easily calculated in Excel by using the STDEV function. However, in order to apply this formula, historical data on property investment performance is needed.
In the United States property investment performance data is available in the United States from the National Council of Real Estate Investment Fiduciaries (NCREIF) which tracks the performance of institutional real estate investments by property type nationally and for the largest metropolitan areas. The four major property types for which historical quarterly performance data is provided by NCREIF include apartments, office, retail and industrial. The data starts from 1994 so there is more than 20 years of data of investment performance by property type. These historical series can be used to estimate the historical volatility (standard deviation) of returns for each property type.
Real estate investors should be very careful in using standard deviation measures that are based on historical volatility, especially for short and medium-term holding periods. The problem with this measure is that it tells us nothing about the current state of the market, and particularly whether it is oversupplied and by how much, which is a major risk when investing in a particular property type.Sivitanides et al. suggest that a better approach to measuring the risk/uncertainty of future cash flows of a property investment is to use econometric techniques to forecast market rents for the market and property type under consideration for investment and use the econometrically measured error of the forecast as the measure of the risk of the investment. By using the forecast error the analyst can develop confidence intervals and a probability distribution for expected rental levels and by extension for the expected internal rate of return of the investment.
As far as the local market risk is concerned, it is important to understand the degree of real estate market segmentation, or in other words, the geographical boundaries within which demand for the particular property type and product interacts with supply to determine prices and rents.Empirical research in the US has established that national real estate markets are segmented along metropolitan boundaries. Such segmentation is the result of idiosyncratic economic and real estate market structures at the local level that elicit differential metropolitan market behavior. The differential real estate investment performance across metropolitan areas can be verified by looking at historical real estate investment returns for major metropolitan markets as reported by the National Council of Real Estate Investment Fiduciaries (NCREIF). NCREIF maintains data on a large number of properties held by major institutional investors in the United States. The reported investment returns are based on the performance of these properties.
Given thedifferential property investment behavior across metropolitan boundaries, it can be argued that metropolitan real estate markets within a country define a universe of real estate investment opportunities characterized by different return prospects and risk profiles. The development, therefore, of a solid national real estate investment strategy requires a systematic evaluation of this universe of investment opportunities and the selection of the combination of markets that is more likely to provide the investor’s targeted return at minimum risk. Such an evaluation could be the first step of an interactive process that combines a “top-down” and a “bottom-up” approach.
A preliminary optimal allocation across metropolitan markets can serve as the starting guiding concept for targeting markets that will be continually refined to incorporate the realities and constraints encountered in the marketplace as the real estate portfolio building process moves on. The derivation of such a preliminary optimal allocation requires the development of a methodology for quantifying expected returns and the risk by property typein each metropolitan market.
Sources of Real Estate Risk Differentials across Metropolitan Markets
Real estate risk differs across metropolitan markets as a result of differential exposure to factors that may threaten the viability of a real estate investment. These factors can be classified into two groups: a) those contributing to the deterioration of the income-earning capacity of a property, and b) those adversely affecting its resale price (although there is a significant overlapping between these two groups of factors).
The major threats to the income-earning capacity of a property are increasing vacanciesand declining rents. Increasing vacancies, on one hand, are the result of oversupply conditions in the market within which the property competes for tenants, and/or low absorption of space. Rent reductions, on the other hand, are the result of low absorption and high vacancy rates, as has been shown by empirical studies in the apartment, office and industrial markets.
Given these dynamics, we can identify three factors shaping the differential real estate risk profiles of metropolitan real estate markets.The first factor is the prevailing vacancy rate, which varies considerably across metropolitan markets. The second factor is the probability of unfavorable developments in a given metropolitan area during the anticipated holding period of a property investment. Such unfavorable developments include unexpected economic downturns or overbuilding.
The probability of a local economic downturn may vary across markets because of differences in their industrial mix, the current state of their economies, and the strength of their comparative advantage in terms of firm and worker amenities. Firm and worker amenities are important factors in urban growth as they affect an area’s attractiveness to companies and population. The probability of excessive construction may also vary because of inter-market differences in the sensitivity of capital flows to increasing rents, the capacity of the local development industry, the regulatory environment that may facilitate or slow down development, and land availability. Given such variations, markets with a higher probability for reduced absorption or excessive construction should be considered as riskier than markets with a lower probability of experiencing such scenarios.
Finally, the third relevant factor is the sensitivity of absorption to employment declines and sensitivity of rents to increasing vacancy rates and low absorption. Differences in such sensitivities across metropolitan markets have been empirically verified and are primarily due to differences in a market’s tenant base mix, the composition of its real estate inventories, the quality mix of the different locations that compose the urban property market, and its submarket and spatial configurations. These differences imply that the negative impact of unfavorable developments on absorption and rents will be greater in the markets in which these sensitivities are higher (all other things being equal).
In terms of the second group of real estate risk factors, the main threat to a property’s resale price, beyond those affecting net operating income (NOI), is the risk that the property will be sold at an exit capitalization rate higher than the one at which it was bought (going-in cap rate). Empirical evidence has shown that the time path of metro-specific capitalization rates is determined to a significant extent by local market conditions. Since such local market conditions differ in terms of their potential volatility, the capital market risk component should also vary across metropolitan markets.
References
Sivitanidou, R. and P. Sivitanides. 1999. “Office Capitalization Rates: Real Estate and Capital Market Influences.” Journal of Real Estate Finance and Economics, Vol. 18, No. 3, pp: 297-322
Sivitanides, P.S., J. Southward, R.G. Torto, and W.C. Wheaton. (1999). Evaluating Risk in Real Estate,Real Estate Finance, 16, 15–22.
Kolbe, P. T., & Greer, G. E. (Author), Gaylon E. Greer. (2012).Investment Analysis for Real Estate Decisions, 8th Edition.Dearborn Real Estate Education.
Sivitanides, P. 2008. Real Estate Investing for Double-Digit Returns. BookSurge Publishing.
Geltner, M., Miller, N. G., Clayton, J., &Eichholtz, P. (2013).Commercial Real Estate Analysis and Investments (with CD-ROM). Oncourse Learning.
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